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      Cross-cultural differences in visual attention: a computational modelling study

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      BMC Neuroscience
      BioMed Central
      24th Annual Computational Neuroscience Meeting: CNS*2015
      18-23 July 2015

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          Abstract

          Literature in visual perception has identified that there are cross-cultural differences in visual perception [1]. Research comparing members of interdepended and collectivist East Asian cultures with independent and individualist European American cultures into picture perception showed that East Asians are more likely to attend the perceptual field as a whole and to focus on context and Westerns to focus on the salient foreground objects [1]. Research on cross-cultural differences has focused on investigating cross-cultural differences related to bottom-up information. Furthermore, research that experimentally manipulated the cultural norms of individualism and collectivism groups managed to attenuate cultural-specific preferences for social factors beneficial in human motivation [2]. Investigating the underlying mechanisms involved in these differences is very important as it can affect everyday tasks, advertisement and many other aspects of our everyday life. Here we present the first steps of this work, investigating the underlying processes in cross-cultural differences using computational modelling studies. The computational model is based on the spiking Search over Space and Time (sSoTS) model [3], that has been used to simulate Visual Attention task. sSoTS has incorporated mechanisms that allows us to investigate both bottom-up and top-down processes. We show that sSoTS can successfully simulate cross-cultural differences in Visual attention involving bottom-up tasks. Moreover, we expand the studies by making predictions from the computational modelling studies for cross-cultural differences and top-down tasks.

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          Culture and the physical environment. Holistic versus analytic perceptual affordances.

          Westerners' perceptions tend to focus on salient foreground objects, whereas Asians are more inclined to focus on contexts. We hypothesized that such culturally specific patterns of attention may be afforded by the perceptual environment of each culture. In order to test this hypothesis, we randomly sampled pictures of scenes from small, medium, and large cities in Japan and the United States. Using both subjective and objective measures, Study 1 demonstrated that Japanese scenes were more ambiguous and contained more elements than American scenes. Japanese scenes thus may encourage perception of the context more than American scenes. In Study 2, pictures of locations in cities were presented as primes, and participants' subsequent patterns of attention were measured. Both Japanese and American participants primed with Japanese scenes attended more to contextual information than did those primed with American scenes. These results provide evidence that culturally characteristic environments may afford distinctive patterns of perception.
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            Bridging the gap between physiology and behavior: evidence from the sSoTS model of human visual attention.

            We present the case for a role of biologically plausible neural network modeling in bridging the gap between physiology and behavior. We argue that spiking-level networks can allow "vertical" translation between physiological properties of neural systems and emergent "whole-system" performance-enabling psychological results to be simulated from implemented networks and also inferences to be made from simulations concerning processing at a neural level. These models also emphasize particular factors (e.g., the dynamics of performance in relation to real-time neuronal processing) that are not highlighted in other approaches and that can be tested empirically. We illustrate our argument from neural-level models that select stimuli by biased competition. We show that a model with biased competition dynamics can simulate data ranging from physiological studies of single-cell activity (Study 1) to whole-system behavior in human visual search (Study 2), while also capturing effects at an intermediate level, including performance breakdown after neural lesion (Study 3) and data from brain imaging (Study 4). We also show that, at each level of analysis, novel predictions can be derived from the biologically plausible parameters adopted, which we proceed to test (Study 5). We argue that, at least for studying the dynamics of visual attention, the approach productively links single-cell to psychological data.
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              Author and article information

              Contributors
              Conference
              BMC Neurosci
              BMC Neurosci
              BMC Neuroscience
              BioMed Central
              1471-2202
              2015
              4 December 2015
              : 16
              : Suppl 1
              : P204
              Affiliations
              [1 ]Department of Psychology, Birmingham City University, Birmingham, B422SU, UK
              [2 ]Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, UK
              Article
              1471-2202-16-S1-P204
              10.1186/1471-2202-16-S1-P204
              4699012
              f3d5de30-3815-4887-92b2-02f44a1a97b4
              Copyright © 2015 Mavritsaki and Rentzelas

              This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

              24th Annual Computational Neuroscience Meeting: CNS*2015
              Prague, Czech Republic
              18-23 July 2015
              Categories
              Poster Presentation

              Neurosciences
              Neurosciences

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